2011
DOI: 10.48550/arxiv.1106.4730
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Multilevel Monte Carlo method for jump-diffusion SDEs

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“…Using Hölder's inequality, the bound max(R τ , R f τ ) ≤ 2 and standard results for a Poisson process, the first term can be bounded using weak convergence results for the constant rate process, and the second term can be bounded using the corresponding strong convergence results [46]. This guarantees that the multilevel procedure does converge to the correct value.…”
Section: Mlmc For Path-dependent Ratesmentioning
confidence: 96%
See 1 more Smart Citation
“…Using Hölder's inequality, the bound max(R τ , R f τ ) ≤ 2 and standard results for a Poisson process, the first term can be bounded using weak convergence results for the constant rate process, and the second term can be bounded using the corresponding strong convergence results [46]. This guarantees that the multilevel procedure does converge to the correct value.…”
Section: Mlmc For Path-dependent Ratesmentioning
confidence: 96%
“…Such differences will give an O(1) difference in the payoff value, and hence the multilevel variance will be O(h). A more detailed analysis of this is given in [46].…”
Section: Mlmc For Path-dependent Ratesmentioning
confidence: 99%